SURFACE-Bind
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  1. GPCR
  2. Q9NPG1

  • GPCR
    • A3KFT3
    • A4D2G3
    • A6NCV1
    • A6ND48
    • A6NDH6
    • A6NDL8
    • A6NET4
    • A6NF89
    • A6NGY5
    • A6NH00
    • A6NHA9
    • A6NHG9
    • A6NIJ9
    • A6NJZ3
    • A6NKK0
    • A6NL08
    • A6NL26
    • A6NM03
    • A6NM76
    • A6NMS3
    • A6NMU1
    • A6NMZ5
    • A6NND4
    • B2RN74
    • O00144
    • O00155
    • O00222
    • O00270
    • O00398
    • O00421
    • O00590
    • O14581
    • O14626
    • O14842
    • O14843
    • O15218
    • O15303
    • O15354
    • O15529
    • O15552
    • O43193
    • O43194
    • O43603
    • O43613
    • O43614
    • O43749
    • O43869
    • O60353
    • O60403
    • O60404
    • O60412
    • O60431
    • O60755
    • O75084
    • O75388
    • O75473
    • O75899
    • O76000
    • O76001
    • O76002
    • O76099
    • O76100
    • O95006
    • O95007
    • O95013
    • O95047
    • O95136
    • O95221
    • O95222
    • O95371
    • O95665
    • O95800
    • O95838
    • O95918
    • O95977
    • P0C7N1
    • P0C7N5
    • P0C7N8
    • P0C7T2
    • P0C7T3
    • P0C604
    • P0C617
    • P0C623
    • P0C626
    • P0C628
    • P0C629
    • P0C645
    • P0C646
    • P03999
    • P04201
    • P07550
    • P08172
    • P08173
    • P08588
    • P08908
    • P08912
    • P08913
    • P11229
    • P13945
    • P14416
    • P18089
    • P18825
    • P20309
    • P21452
    • P21453
    • P21462
    • P21554
    • P21728
    • P21730
    • P21731
    • P21917
    • P21918
    • P25021
    • P25024
    • P25025
    • P25089
    • P25100
    • P25103
    • P25105
    • P25106
    • P25116
    • P25929
    • P28221
    • P28222
    • P28335
    • P28566
    • P29274
    • P29275
    • P29371
    • P30411
    • P30518
    • P30542
    • P30550
    • P30559
    • P30872
    • P30874
    • P30939
    • P30953
    • P30954
    • P30968
    • P30988
    • P31391
    • P32238
    • P32241
    • P32245
    • P32246
    • P32247
    • P32248
    • P32249
    • P32302
    • P32745
    • P33032
    • P34969
    • P34972
    • P34981
    • P34982
    • P34995
    • P34998
    • P35346
    • P35367
    • P35368
    • P35372
    • P35408
    • P35410
    • P35414
    • P35462
    • P37288
    • P41143
    • P41145
    • P41146
    • P41180
    • P41231
    • P41586
    • P41587
    • P41968
    • P43088
    • P43115
    • P43116
    • P43119
    • P43220
    • P43657
    • P46089
    • P46092
    • P46093
    • P46095
    • P46663
    • P47211
    • P47775
    • P47804
    • P47872
    • P47881
    • P47883
    • P47884
    • P47887
    • P47888
    • P47890
    • P47893
    • P47898
    • P47900
    • P47901
    • P48145
    • P48146
    • P48546
    • P49019
    • P49146
    • P49190
    • P49238
    • P49286
    • P49683
    • P49685
    • P50052
    • P50391
    • P50406
    • P51582
    • P51677
    • P51684
    • P51686
    • P55085
    • P58170
    • P58173
    • P58180
    • P58181
    • P58182
    • P59533
    • P59534
    • P59540
    • P59541
    • P59542
    • P59543
    • P59922
    • P60893
    • P61073
    • Q5JQS5
    • Q5JRS4
    • Q5NUL3
    • Q5T6X5
    • Q5T848
    • Q5TZ20
    • Q5UAW9
    • Q5VW38
    • Q6DWJ6
    • Q6IEU7
    • Q6IEV9
    • Q6IEY1
    • Q6IEZ7
    • Q6IF00
    • Q6IF42
    • Q6IF63
    • Q6IF82
    • Q6IF99
    • Q6IFG1
    • Q6IFH4
    • Q6IFN5
    • Q6NV75
    • Q6PRD1
    • Q6U736
    • Q6W5P4
    • Q7RTX0
    • Q7RTX1
    • Q7Z5H5
    • Q7Z601
    • Q7Z602
    • Q8IXE1
    • Q8IYL9
    • Q8N0Y3
    • Q8N0Y5
    • Q8N6U8
    • Q8N127
    • Q8N146
    • Q8N148
    • Q8N162
    • Q8N349
    • Q8N628
    • Q8NDV2
    • Q8NFJ5
    • Q8NFJ6
    • Q8NFN8
    • Q8NFZ6
    • Q8NG75
    • Q8NG76
    • Q8NG77
    • Q8NG78
    • Q8NG80
    • Q8NG81
    • Q8NG83
    • Q8NG84
    • Q8NG85
    • Q8NG92
    • Q8NG94
    • Q8NG95
    • Q8NG98
    • Q8NG99
    • Q8NGA0
    • Q8NGA1
    • Q8NGA2
    • Q8NGA5
    • Q8NGA6
    • Q8NGA8
    • Q8NGB2
    • Q8NGB4
    • Q8NGB6
    • Q8NGB8
    • Q8NGB9
    • Q8NGC0
    • Q8NGC1
    • Q8NGC2
    • Q8NGC3
    • Q8NGC4
    • Q8NGC5
    • Q8NGC6
    • Q8NGC7
    • Q8NGC8
    • Q8NGC9
    • Q8NGD0
    • Q8NGD2
    • Q8NGD3
    • Q8NGD4
    • Q8NGD5
    • Q8NGE0
    • Q8NGE1
    • Q8NGE2
    • Q8NGE3
    • Q8NGE5
    • Q8NGE7
    • Q8NGE8
    • Q8NGE9
    • Q8NGF0
    • Q8NGF1
    • Q8NGF3
    • Q8NGF4
    • Q8NGF6
    • Q8NGF7
    • Q8NGF8
    • Q8NGF9
    • Q8NGG0
    • Q8NGG1
    • Q8NGG2
    • Q8NGG3
    • Q8NGG4
    • Q8NGG5
    • Q8NGG6
    • Q8NGG7
    • Q8NGG8
    • Q8NGH3
    • Q8NGH5
    • Q8NGH6
    • Q8NGH7
    • Q8NGH8
    • Q8NGH9
    • Q8NGI0
    • Q8NGI1
    • Q8NGI2
    • Q8NGI3
    • Q8NGI4
    • Q8NGI6
    • Q8NGI7
    • Q8NGI8
    • Q8NGI9
    • Q8NGJ0
    • Q8NGJ1
    • Q8NGJ2
    • Q8NGJ3
    • Q8NGJ4
    • Q8NGJ5
    • Q8NGJ6
    • Q8NGJ7
    • Q8NGJ8
    • Q8NGK0
    • Q8NGK1
    • Q8NGK2
    • Q8NGK3
    • Q8NGK4
    • Q8NGK5
    • Q8NGK6
    • Q8NGK9
    • Q8NGL0
    • Q8NGL1
    • Q8NGL2
    • Q8NGL3
    • Q8NGL4
    • Q8NGL6
    • Q8NGL7
    • Q8NGL9
    • Q8NGM1
    • Q8NGM8
    • Q8NGM9
    • Q8NGN0
    • Q8NGN1
    • Q8NGN2
    • Q8NGN3
    • Q8NGN4
    • Q8NGN5
    • Q8NGN6
    • Q8NGN7
    • Q8NGN8
    • Q8NGP0
    • Q8NGP2
    • Q8NGP3
    • Q8NGP4
    • Q8NGP6
    • Q8NGP8
    • Q8NGP9
    • Q8NGQ1
    • Q8NGQ2
    • Q8NGQ3
    • Q8NGQ4
    • Q8NGQ5
    • Q8NGQ6
    • Q8NGR1
    • Q8NGR2
    • Q8NGR3
    • Q8NGR4
    • Q8NGR5
    • Q8NGR6
    • Q8NGR8
    • Q8NGR9
    • Q8NGS0
    • Q8NGS1
    • Q8NGS2
    • Q8NGS3
    • Q8NGS4
    • Q8NGS5
    • Q8NGS6
    • Q8NGS7
    • Q8NGS8
    • Q8NGS9
    • Q8NGT0
    • Q8NGT1
    • Q8NGT2
    • Q8NGT7
    • Q8NGT9
    • Q8NGU1
    • Q8NGU4
    • Q8NGU9
    • Q8NGV0
    • Q8NGV5
    • Q8NGV6
    • Q8NGV7
    • Q8NGW1
    • Q8NGW6
    • Q8NGX0
    • Q8NGX1
    • Q8NGX2
    • Q8NGX3
    • Q8NGX5
    • Q8NGX6
    • Q8NGX8
    • Q8NGX9
    • Q8NGY0
    • Q8NGY1
    • Q8NGY2
    • Q8NGY3
    • Q8NGY5
    • Q8NGY6
    • Q8NGY7
    • Q8NGY9
    • Q8NGZ0
    • Q8NGZ2
    • Q8NGZ3
    • Q8NGZ4
    • Q8NGZ5
    • Q8NGZ6
    • Q8NGZ9
    • Q8NH00
    • Q8NH01
    • Q8NH02
    • Q8NH03
    • Q8NH04
    • Q8NH05
    • Q8NH06
    • Q8NH07
    • Q8NH09
    • Q8NH10
    • Q8NH16
    • Q8NH18
    • Q8NH19
    • Q8NH21
    • Q8NH37
    • Q8NH40
    • Q8NH41
    • Q8NH42
    • Q8NH43
    • Q8NH48
    • Q8NH49
    • Q8NH50
    • Q8NH51
    • Q8NH53
    • Q8NH54
    • Q8NH55
    • Q8NH56
    • Q8NH57
    • Q8NH59
    • Q8NH60
    • Q8NH61
    • Q8NH63
    • Q8NH64
    • Q8NH69
    • Q8NH70
    • Q8NH72
    • Q8NH73
    • Q8NH74
    • Q8NH76
    • Q8NH79
    • Q8NH80
    • Q8NH81
    • Q8NH83
    • Q8NH85
    • Q8NH87
    • Q8NH90
    • Q8NH92
    • Q8NH93
    • Q8NH94
    • Q8NH95
    • Q8NHA4
    • Q8NHA6
    • Q8NHA8
    • Q8NHB1
    • Q8NHB7
    • Q8NHB8
    • Q8NHC4
    • Q8NHC5
    • Q8NHC6
    • Q8NHC7
    • Q8NHC8
    • Q8TCB6
    • Q8TCW9
    • Q8TDS4
    • Q8TDS5
    • Q8TDS7
    • Q8TDT2
    • Q8TDU9
    • Q8TDV2
    • Q8TDV5
    • Q8TE23
    • Q8WZ84
    • Q8WZ92
    • Q8WZ94
    • Q8WZA6
    • Q9BXA5
    • Q9BXC0
    • Q9BXC1
    • Q9BXE9
    • Q9BY21
    • Q9BZJ6
    • Q9BZJ7
    • Q9BZJ8
    • Q9GZK3
    • Q9GZK4
    • Q9GZK6
    • Q9GZK7
    • Q9GZM6
    • Q9GZN0
    • Q9GZP7
    • Q9GZQ6
    • Q9H1C0
    • Q9H1Y3
    • Q9H2C5
    • Q9H2C8
    • Q9H3N8
    • Q9H205
    • Q9H207
    • Q9H208
    • Q9H209
    • Q9H210
    • Q9H228
    • Q9H255
    • Q9H339
    • Q9H340
    • Q9H341
    • Q9H342
    • Q9H343
    • Q9H346
    • Q9H461
    • Q9HB89
    • Q9HBW0
    • Q9HBX8
    • Q9HBX9
    • Q9HC97
    • Q9HCU4
    • Q9NPB9
    • Q9NPC1
    • Q9NPG1
    • Q9NQ84
    • Q9NQN1
    • Q9NS66
    • Q9NS67
    • Q9NSD7
    • Q9NWF4
    • Q9NYM4
    • Q9NYQ6
    • Q9NYQ7
    • Q9NYV7
    • Q9NYV8
    • Q9NYW0
    • Q9NYW1
    • Q9NYW2
    • Q9NYW3
    • Q9NYW5
    • Q9NYW6
    • Q9NYW7
    • Q9NZD1
    • Q9NZH0
    • Q9NZP0
    • Q9NZP2
    • Q9NZP5
    • Q9P1P5
    • Q9P1Q5
    • Q9P296
    • Q9UBS5
    • Q9UBY5
    • Q9UGF5
    • Q9UGF6
    • Q9UGF7
    • Q9UHM6
    • Q9UKL2
    • Q9UKP6
    • Q9ULV1
    • Q9ULW2
    • Q9UNW8
    • Q9UP38
    • Q9UPC5
    • Q9Y2T5
    • Q9Y2T6
    • Q9Y3N9
    • Q9Y4A9
    • Q9Y5N1
    • Q9Y5P0
    • Q9Y5P1
    • Q9Y5X5
    • Q9Y5Y3
    • Q9Y5Y4
    • Q9Y585
    • Q49SQ1
    • Q86SM5
    • Q86SM8
    • Q86VZ1
    • Q96CH1
    • Q96KK4
    • Q96LA9
    • Q96LB0
    • Q96LB1
    • Q96LB2
    • Q96P65
    • Q96P66
    • Q96P67
    • Q96P68
    • Q96P69
    • Q96P88
    • Q96R08
    • Q96R09
    • Q96R27
    • Q96R28
    • Q96R45
    • Q96R47
    • Q96R48
    • Q96R54
    • Q96R67
    • Q96R69
    • Q96R72
    • Q96R84
    • Q96RA2
    • Q96RB7
    • Q96RC9
    • Q96RD0
    • Q96RD1
    • Q96RD2
    • Q96RD3
    • Q96RI0
    • Q96RI9
    • Q96RJ0
    • Q969F8
    • Q969V1
    • Q01718
    • Q01726
    • Q02643
    • Q03431
    • Q13255
    • Q13258
    • Q13304
    • Q13324
    • Q13467
    • Q13585
    • Q13606
    • Q13607
    • Q14330
    • Q14332
    • Q14416
    • Q14439
    • Q14831
    • Q14832
    • Q14833
    • Q15077
    • Q15612
    • Q15617
    • Q15619
    • Q15620
    • Q15622
    • Q15722
    • Q15760
    • Q15761
    • Q16538
    • Q16570
    • Q16581
    • Q16602
    • Q92847
    • Q99463
    • Q99500
    • Q99527
    • Q99677
    • Q99678
    • Q99680
    • Q99705
    • Q99788
    • Q99835

  • IG
    • A6NI73
    • O14931
    • O14931
    • O75015
    • O75019
    • O75022
    • O75023
    • O75054
    • O76036
    • O95185
    • O95256
    • O95944
    • O95976
    • P01589
    • P01833
    • P06126
    • P08637
    • P08887
    • P10912
    • P12314
    • P12318
    • P12319
    • P14778
    • P14784
    • P15151
    • P15260
    • P15509
    • P15812
    • P15813
    • P16471
    • P16871
    • P17181
    • P19235
    • P24394
    • P26951
    • P26992
    • P27930
    • P29016
    • P29017
    • P31785
    • P31994
    • P31995
    • P32927
    • P32942
    • P38484
    • P40189
    • P40238
    • P42701
    • P42702
    • P43146
    • P43626
    • P43627
    • P43628
    • P43629
    • P43630
    • P43631
    • P43632
    • P48357
    • P48551
    • P55899
    • P59901
    • P78310
    • P78552
    • Q2VWP7
    • Q4KMG0
    • Q5DX21
    • Q5T2D2
    • Q5VWK5
    • Q6DN72
    • Q6IA17
    • Q6PI73
    • Q6Q8B3
    • Q6UXG3
    • Q6UXL0
    • Q6UXZ4
    • Q6ZN44
    • Q8IU57
    • Q8IVU1
    • Q8IZJ1
    • Q8N6C5
    • Q8N6P7
    • Q8N109
    • Q8N149
    • Q8N423
    • Q8N743
    • Q8NHK3
    • Q8NHL6
    • Q8NI17
    • Q8TD46
    • Q8TDQ1
    • Q8TDY8
    • Q8WWV6
    • Q9BWV1
    • Q9HB29
    • Q9HBE5
    • Q9HCK4
    • Q9NP60
    • Q9NP99
    • Q9NPH3
    • Q9NSI5
    • Q9NZC2
    • Q9NZN1
    • Q9UGN4
    • Q9UHF4
    • Q9Y6N7
    • Q96LA5
    • Q96LA6
    • Q96MS0
    • Q96P31
    • Q496F6
    • Q969P0
    • Q01113
    • Q01344
    • Q01638
    • Q08334
    • Q08708
    • Q13261
    • Q13478
    • Q13651
    • Q14626
    • Q14627
    • Q14943
    • Q14952
    • Q14953
    • Q14954
    • Q15109
    • Q15762
    • Q92637
    • Q92859
    • Q93033
    • Q99062
    • Q99650
    • Q99665
    • Q99706
    • Q99795

  • Kinase
    • O15146
    • O15197
    • P00533
    • P04626
    • P04629
    • P06213
    • P07333
    • P07949
    • P08069
    • P08581
    • P08922
    • P09619
    • P10721
    • P11362
    • P14616
    • P16066
    • P16234
    • P17342
    • P17948
    • P20594
    • P21709
    • P21802
    • P21860
    • P22455
    • P22607
    • P25092
    • P27037
    • P29317
    • P29320
    • P29322
    • P29323
    • P29376
    • P30530
    • P34925
    • P35590
    • P35916
    • P35968
    • P36888
    • P36894
    • P36896
    • P36897
    • P37023
    • P37173
    • P54753
    • P54756
    • P54760
    • P54762
    • P54764
    • Q5JZY3
    • Q8NER5
    • Q9UF33
    • Q01973
    • Q01974
    • Q02763
    • Q04771
    • Q04912
    • Q06418
    • Q08345
    • Q12866
    • Q13308
    • Q13705
    • Q13873
    • Q15303
    • Q15375
    • Q16288
    • Q16620
    • Q16671
    • Q16832

  • Other_receptors
    • O00206
    • O00220
    • O14522
    • O14786
    • O14836
    • O15031
    • O15455
    • O43157
    • O60462
    • O60486
    • O60602
    • O60603
    • O60895
    • O60896
    • O75051
    • O75074
    • O75096
    • O75197
    • O75509
    • O75578
    • O75581
    • P01130
    • P01133
    • P05106
    • P05107
    • P05556
    • P06756
    • P08138
    • P08514
    • P08575
    • P08648
    • P10586
    • P11215
    • P13612
    • P14151
    • P16109
    • P16144
    • P16581
    • P17301
    • P18084
    • P18433
    • P18564
    • P19438
    • P20333
    • P20701
    • P20702
    • P23229
    • P23467
    • P23468
    • P23470
    • P23471
    • P25445
    • P25942
    • P26006
    • P26010
    • P26012
    • P28827
    • P28908
    • P34741
    • P36941
    • P38570
    • P43489
    • P46531
    • P51805
    • P53708
    • P56199
    • P58400
    • P58401
    • P78357
    • P98155
    • P98164
    • Q5VYJ5
    • Q7Z4F1
    • Q8NAC3
    • Q8NFM7
    • Q8NFR9
    • Q8WY21
    • Q8WYK1
    • Q9BXR5
    • Q9BZ76
    • Q9C0A0
    • Q9HAV5
    • Q9HCM2
    • Q9HD43
    • Q9HDB5
    • Q9NR96
    • Q9NR97
    • Q9NRM6
    • Q9NS68
    • Q9NYK1
    • Q9NZR2
    • Q9P2S2
    • Q9UBN6
    • Q9UHC6
    • Q9UIW2
    • Q9UKX5
    • Q9ULB1
    • Q9ULL4
    • Q9UM47
    • Q9UMZ3
    • Q9UNE0
    • Q9UPU3
    • Q9Y2C9
    • Q9Y4C0
    • Q9Y4D7
    • Q9Y5U5
    • Q9Y6Q6
    • Q9Y561
    • Q86VZ4
    • Q96F46
    • Q96NU0
    • Q96PQ0
    • Q969Z4
    • Q02223
    • Q04721
    • Q07011
    • Q07954
    • Q12913
    • Q13332
    • Q13349
    • Q13635
    • Q13683
    • Q13797
    • Q14114
    • Q15256
    • Q15262
    • Q15399
    • Q16827
    • Q16849
    • Q92673
    • Q92729
    • Q92932
    • Q92956
    • Q93038
    • Q99466
    • Q99467
    • Q99523

  • SCAR
    • A6BM72
    • O60449
    • P07306
    • P07307
    • P13473
    • P16671
    • P21757
    • P22897
    • P26715
    • P26717
    • P26718
    • P78380
    • P98153
    • Q2HXU8
    • Q5QGZ9
    • Q5VY43
    • Q6UX15
    • Q6UXB4
    • Q6UXN8
    • Q6ZS10
    • Q8IX05
    • Q8NC01
    • Q8WTV0
    • Q8WWQ8
    • Q9BXN2
    • Q9H2X3
    • Q9HCU0
    • Q9NY25
    • Q9NZS2
    • Q9P126
    • Q9UBG0
    • Q9UHP7
    • Q9UQV4
    • Q96E93
    • Q96GP6
    • Q96KG7
    • Q07108
    • Q07444
    • Q12918
    • Q13018
    • Q14162

  • Receptors

On this page

  • General information
  • AlphaFold model
  • Surface representation - binding sites
  • All detected seeds aligned
  • Seed scores per sites
  • Binding site metrics
  • Binding site sequence composition
  • Download
  1. GPCR
  2. Q9NPG1

Q9NPG1

Author

Hamed Khakzad

Published

August 10, 2024

General information

Code
import requests
import urllib3
urllib3.disable_warnings()

def fetch_uniprot_data(uniprot_id):
    url = f"https://rest.uniprot.org/uniprotkb/{uniprot_id}.json"
    response = requests.get(url, verify=False)  # Disable SSL verification
    response.raise_for_status()  # Raise an error for bad status codes
    return response.json()

def display_uniprot_data(data):
    primary_accession = data.get('primaryAccession', 'N/A')
    protein_name = data.get('proteinDescription', {}).get('recommendedName', {}).get('fullName', {}).get('value', 'N/A')
    gene_name = data.get('gene', [{'geneName': {'value': 'N/A'}}])[0]['geneName']['value']
    organism = data.get('organism', {}).get('scientificName', 'N/A')
    
    function_comment = next((comment for comment in data.get('comments', []) if comment['commentType'] == "FUNCTION"), None)
    function = function_comment['texts'][0]['value'] if function_comment else 'N/A'

    # Printing the data
    print(f"UniProt ID: {primary_accession}")
    print(f"Protein Name: {protein_name}")
    print(f"Organism: {organism}")
    print(f"Function: {function}")

# Replace this with the UniProt ID you want to fetch
uniprot_id = "Q9NPG1"
data = fetch_uniprot_data(uniprot_id)
display_uniprot_data(data)
UniProt ID: Q9NPG1
Protein Name: Frizzled-3
Organism: Homo sapiens
Function: Receptor for Wnt proteins. Most of frizzled receptors are coupled to the beta-catenin canonical signaling pathway, which leads to the activation of disheveled proteins, inhibition of GSK-3 kinase, nuclear accumulation of beta-catenin and activation of Wnt target genes. A second signaling pathway involving PKC and calcium fluxes has been seen for some family members, but it is not yet clear if it represents a distinct pathway or if it can be integrated in the canonical pathway, as PKC seems to be required for Wnt-mediated inactivation of GSK-3 kinase. Both pathways seem to involve interactions with G-proteins. Activation by Wnt5A stimulates PKC activity via a G-protein-dependent mechanism. Involved in transduction and intercellular transmission of polarity information during tissue morphogenesis and/or in differentiated tissues. Plays a role in controlling early axon growth and guidance processes necessary for the formation of a subset of central and peripheral major fiber tracts. Required for the development of major fiber tracts in the central nervous system, including: the anterior commissure, the corpus callosum, the thalamocortical, corticothalamic and nigrostriatal tracts, the corticospinal tract, the fasciculus retroflexus, the mammillothalamic tract, the medial lemniscus, and ascending fiber tracts from the spinal cord to the brain. In the peripheral nervous system, controls axon growth in distinct populations of cranial and spinal motor neurons, including the facial branchimotor nerve, the hypoglossal nerve, the phrenic nerve, and motor nerves innervating dorsal limbs. Involved in the migration of cranial neural crest cells. May also be implicated in the transmission of sensory information from the trunk and limbs to the brain. Controls commissural sensory axons guidance after midline crossing along the anterior-posterior axis in the developing spinal cord in a Wnt-dependent signaling pathway. Together with FZD6, is involved in the neural tube closure and plays a role in the regulation of the establishment of planar cell polarity (PCP), particularly in the orientation of asymmetric bundles of stereocilia on the apical faces of a subset of auditory and vestibular sensory cells located in the inner ear. Promotes neurogenesis by maintaining sympathetic neuroblasts within the cell cycle in a beta-catenin-dependent manner (By similarity)

More information:   

AlphaFold model

Surface representation - binding sites

The computed point cloud for pLDDT > 0.6. Each atom is sampled on average by 10 points.

To see the predicted binding interfaces, you can choose color theme “uncertainty”.

  • Go to the “Controls Panel”

  • Below “Components”, to the right, click on “…”

  • “Set Coloring” by “Atom Property”, and “Uncertainty/Disorder”

All detected seeds aligned

Seed scores per sites

Code
import re
import pandas as pd
import os
import plotly.express as px

ID = "Q9NPG1"
data_list = []

name_pattern = re.compile(r'name: (\S+)')
score_pattern = re.compile(r'score: (\d+\.\d+)')
desc_dist_score_pattern = re.compile(r'desc_dist_score: (\d+\.\d+)')

directory = f"/Users/hamedkhakzad/Research_EPFL/1_postdoc_project/Surfaceome_web_app/www/Surfaceome_top100_per_site/{ID}_A"

for filename in os.listdir(directory):
    if filename.startswith("output_sorted_") and filename.endswith(".score"):
        filepath = os.path.join(directory, filename)
        with open(filepath, 'r') as file:
            for line in file:
                name_match = name_pattern.search(line)
                score_match = score_pattern.search(line)
                desc_dist_score_match = desc_dist_score_pattern.search(line)
                
                if name_match and score_match and desc_dist_score_match:
                    name = name_match.group(1)
                    score = float(score_match.group(1))
                    desc_dist_score = float(desc_dist_score_match.group(1))
                    
                    simple_filename = filename.replace("output_sorted_", "").replace(".score", "")
                    data_list.append({
                        'name': name[:-1],
                        'score': score,
                        'desc_dist_score': desc_dist_score,
                        'file': simple_filename
                    })

data = pd.DataFrame(data_list)

fig = px.scatter(
    data,
    x='score',
    y='desc_dist_score',
    color='file',
    title='Score vs Desc Dist Score',
    labels={'score': 'Score', 'desc_dist_score': 'Desc Dist Score'},
    hover_data={'name': True}
)

fig.update_layout(
    legend_title_text='File',
    legend=dict(
        yanchor="top",
        y=0.99,
        xanchor="left",
        x=1.05
    )
)

fig.show()

Binding site metrics

Code
import pandas as pd
pd.options.mode.chained_assignment = None
import plotly.express as px

df_total = pd.read_csv('/Users/hamedkhakzad/Research_EPFL/1_postdoc_project/Surfaceome_web_app/www/database/df_flattened.csv')
df_plot = df_total[df_total['acc_flat'] == ID]
df_plot ['Total seeds'] = df_plot.loc[:,['seedss_a','seedss_b']].sum(axis=1)
df_plot.loc[:, ["acc_flat", "main_classs", "sub_classs", "seedss_a", "seedss_b", "areass", "bsss", "hpss"]]
acc_flat main_classs sub_classs seedss_a seedss_b areass bsss hpss
1666 Q9NPG1 Receptors GPCR 120 698 1062.161229 507 14.0
Code
import math
import matplotlib.pyplot as plt

features = ['seedss_a', 'seedss_b', 'areass', 'hpss']
titles = ['Alpha seeds', 'Beta seeds', 'Area', 'Hydrophobicity']
num_features = len(features)

if len(df_plot) > 8:
    num_rows = 2
    num_cols = 2
else:
    num_rows = 1
    num_cols = 4

fig, axes = plt.subplots(nrows=num_rows, ncols=num_cols, figsize=(9, num_rows * 5))

axes = axes.flatten()
positions = range(1, len(df_plot) + 1)

for i, feature in enumerate(features):
    title = titles[i]
    axes[i].bar(positions, df_plot[feature], color=['blue', 'orange', 'green', 'red', 'purple', 'brown'])
    axes[i].set_title(title, fontsize=13)
    axes[i].set_xticks(positions)
    axes[i].set_xticklabels(df_plot['bsss'], rotation=90)
    axes[i].set_xlabel("Center residues", fontsize=13)
    axes[i].set_ylabel(title, fontsize=13)

for j in range(len(features), len(axes)):
    fig.delaxes(axes[j])

plt.tight_layout()
plt.show()

Binding site sequence composition

Code
amino_acid_map = {
    'ALA': 'A', 'ARG': 'R', 'ASN': 'N', 'ASP': 'D', 'CYS': 'C',
    'GLN': 'Q', 'GLU': 'E', 'GLY': 'G', 'HIS': 'H', 'ILE': 'I',
    'LEU': 'L', 'LYS': 'K', 'MET': 'M', 'PHE': 'F', 'PRO': 'P',
    'SER': 'S', 'THR': 'T', 'TRP': 'W', 'TYR': 'Y', 'VAL': 'V'
}

from collections import Counter
from ast import literal_eval
from matplotlib.gridspec import GridSpec
import warnings
warnings.filterwarnings("ignore", message="Attempting to set identical low and high xlims")

def convert_to_single_letter(aa_list):
    if type(aa_list) == str:
        aa_list = literal_eval(aa_list)
    return [amino_acid_map[aa] for aa in aa_list]

def create_sequence_visualizations(df, max_letters_per_row=20):
    for idx, row in df.iterrows():
        bsss = row['bsss']
        AAss = row['AAss']
        single_letter_sequence = convert_to_single_letter(AAss)
        
        freq_counter = Counter(single_letter_sequence)
        total_aa = len(single_letter_sequence)
        frequencies = {aa: freq / total_aa for aa, freq in freq_counter.items()}
        
        cmap = plt.get_cmap('viridis')
        norm = plt.Normalize(0, max(frequencies.values()) if frequencies else 1)
        
        n_rows = (len(single_letter_sequence) + max_letters_per_row - 1) // max_letters_per_row
        fig = plt.figure(figsize=(max_letters_per_row * 0.6, n_rows * 1.2 + 0.5))
        
        gs = GridSpec(n_rows + 1, 1, height_ratios=[1] * n_rows + [0.1], hspace=0.3)
        
        for row_idx in range(n_rows):
            start_idx = row_idx * max_letters_per_row
            end_idx = min((row_idx + 1) * max_letters_per_row, len(single_letter_sequence))
            ax = fig.add_subplot(gs[row_idx, 0])
            ax.set_xlim(0, max_letters_per_row)
            ax.set_ylim(0, 1)
            ax.axis('off')
            
            for i, aa in enumerate(single_letter_sequence[start_idx:end_idx]):
                freq = frequencies[aa]
                color = cmap(norm(freq))
                ax.text(i + 0.5, 0.5, aa, ha='center', va='center', fontsize=24, color=color, fontweight='bold')
        
        cbar_ax = fig.add_subplot(gs[-1, 0])
        sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
        sm.set_array([])
        cbar = plt.colorbar(sm, cax=cbar_ax, orientation='horizontal')
        cbar.set_label('Frequency', fontsize=12)
        cbar.ax.tick_params(labelsize=12)
        
        plt.suptitle(f"Center residue {bsss}", fontsize=14)
        plt.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.1)
        plt.show()
            
create_sequence_visualizations(df_plot)

Download

To download all the seeds and score files for this entry Click Here!

Q9NPC1
Q9NQ84